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Research on image segmentation method based on improved Snake model

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Abstract

Image segmentation is one of the key research fields in computer vision, and the research of image segmentation methods based on active contour model has been continuously advanced in recent years. Aiming at the defect problem such as traditional Snake model algorithm is more sensitive to the noise of the original target image, it is proposed that an improved segmentation algorithm based on bilateral filter to replace the original Gaussian filter of the traditional Snake model, to reduce the noise of the original target image, by weighing the spatial domain weights and domain weights of the pixel points, so as to achieve the purpose of edge denising, so that the original target image edge contour can be further optimized and extracted; By using the snake model before and after improvement, we performed a qualitative and comparative analysis for the extraction effects on edge contour of the same original target image object, and it was verified that the improved snake model proposed here is more accurate and effective. The accuracy and effectiveness of the improved model here are objectively and quantitatively verified, according to the number of sampling points extracted, peak of noise-signal ratio(SNR) of the result map extracted and image quality of original target image object edge profile.

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All data, models, and code generated or used during the study appear in the submitted article.

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Acknowledgements

The authors would like to thank the basic research program (natural science) project supported by department of science and technology of Guizhou province (Contract no: QianKeHe foundation-ZK [2023] general 031).The authors would like to thank the project supported by Science and Technology Program of the Guizhou Provincial Science and Technology Agency (Contract number:QianKeHeBasic[2020]1Y156). The authors would like to thank Guizhou Key Laboratory of Big Data Statistical Analysis( No.[2019]5103),.The funders had active role in study design, data collection and analysis, decision to publish, and preparation of the manuscript.

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Authors and Affiliations

  1. Information Institute, Guizhou University of Financial and Economics, Guiyang, 550025, China

    Mei Zhang, Dan Meng, Yongtao Pei & Jinghua Wen

  2. Guizhou Key Laboratory of Big Data Statistical Analysis (No.[2019]5103), Guiyang, 550025, China

    Mei Zhang

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  1. Mei Zhang
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  2. Dan Meng
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Correspondence to Mei Zhang.

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Zhang, M., Meng, D., Pei, Y. et al. Research on image segmentation method based on improved Snake model. Multimed Tools Appl 83, 13977–13994 (2024). https://doi.org/10.1007/s11042-023-15822-y

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  • DOI: https://doi.org/10.1007/s11042-023-15822-y

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